{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- coding:utf-8 -*-\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import networkx as nx\n",
    "import jieba\n",
    "from jieba import posseg as pseg\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import pypinyin as pypy\n",
    "from node2vec import Node2Vec\n",
    "from scipy.spatial.distance import cosine\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from  torch.nn import functional as F\n",
    "import torch.optim as optim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# below is a context graph, that represents words that are adjencent to each other with count as weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Dumping model to file cache /tmp/jieba.cache\n",
      "Loading model cost 0.611 seconds.\n",
      "Prefix dict has been built succesfully.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with open(\"data/data.txt\",\"r\") as f:\n",
    "    data = f.readlines()\n",
    "full_data = {}\n",
    "title = None\n",
    "word_pos = {}\n",
    "for l in data:\n",
    "    if l.startswith(\"#\"):\n",
    "        title = l.strip(\"#\").strip(\"\\n\").strip()\n",
    "        full_data[title]=[]\n",
    "    else:\n",
    "        if l!=\"\\n\":\n",
    "            full_data[title].append([w for w,_ in pseg.lcut(l.strip(\"\\n\"))])\n",
    "            for w,tag in pseg.lcut(l.strip(\"\\n\")):\n",
    "                if title==\"libra\":\n",
    "                    word_pos[w]=tag\n",
    "data = full_data[\"libra\"]\n",
    "G =  nx.DiGraph()\n",
    "for s in data:\n",
    "    G.add_nodes_from(s)\n",
    "    for i,w in enumerate(s[1:]):\n",
    "        if (s[i],w) not in G.edges:\n",
    "            G.add_edge(s[i],w,weight=1)\n",
    "        else:\n",
    "            G[s[i]][w][\"weight\"]+=1\n",
    "plt.figure(figsize=(20,20))\n",
    "nx.draw(G,with_label=True,font_weight=\"bold\")\n",
    "pd.Series(nx.pagerank(G)).sort_values(ascending=False)\n",
    "left1 = {n:set() for n in G.nodes}\n",
    "left2 = {n:set() for n in G.nodes}\n",
    "right1 = {n:set() for n in G.nodes}\n",
    "right2 = {n:set() for n in G.nodes}\n",
    "for n in G.nodes:\n",
    "    for l1 in G.predecessors(n):\n",
    "        left1[n]|=set([l1])\n",
    "        left2[n]|=set([l1])\n",
    "        for l2 in G.predecessors(l1):\n",
    "            left2[n]|=set([l2])\n",
    "    for r1 in G.successors(n):\n",
    "        right1[n]|=set([r1])\n",
    "        right2[n]|=set([r1])\n",
    "        for r2 in G.successors(r1):\n",
    "            right2[n]|=set([r2])\n",
    "context1 = {n:set() for n in G.nodes}\n",
    "context2 = {n:set() for n in G.nodes}\n",
    "for w in context1.keys():\n",
    "    context1[w] = left1[w]|right1[w]\n",
    "    context2[w] = left2[w]|right2[w]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set()"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(list(G.nodes()))-set(word_pos.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# the words similarity are calculated with jaccard index on the target word context, meaning words appear next to the target word."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "below are the found similar words with window size 1, left1 and right1\n",
      "日内瓦 瑞士 1.0\n",
      "阻止 要求 1.0\n",
      "都 上线 1.0\n",
      "管制 数字 1.0\n",
      "提问 事实 1.0\n",
      "称 表示 1.0\n"
     ]
    }
   ],
   "source": [
    "similarity_matrix = pd.DataFrame(data=np.zeros((len(context1.keys()),len(context1.keys()))),index=list(context1.keys()),columns=list(context1.keys()))\n",
    "for row in similarity_matrix.index:\n",
    "    for col in similarity_matrix.columns:\n",
    "        if row!=col:\n",
    "            similarity_matrix.loc[row,col]=len(context1[row]&context1[col])/len(context1[row]|context1[col])\n",
    "print(\"below are the found similar words with window size 1, left1 and right1\")\n",
    "for i,row in enumerate(similarity_matrix.index):\n",
    "    for j,col in enumerate(similarity_matrix.columns):\n",
    "        if i>j:\n",
    "            if similarity_matrix.loc[row,col]>0.5:\n",
    "                print(row,col,similarity_matrix.loc[row,col])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "below are the found similar words with window size 2, left2 and right2\n",
      "日内瓦 瑞士 1.0\n",
      "提问 事实 1.0\n",
      "称 表示 1.0\n",
      "需要 据 0.9166666666666666\n",
      "需要 今天 0.9166666666666666\n",
      "需要 那么 0.9166666666666666\n",
      "需要 但 0.9166666666666666\n",
      "需要 对 0.9166666666666666\n",
      "现在 需要 0.9166666666666666\n",
      "透露 日讯 0.9090909090909091\n",
      "透露 报道 0.9090909090909091\n",
      "透露 中 0.9090909090909091\n",
      "透露 强调 0.9523809523809523\n",
      "透露 上线 0.9090909090909091\n",
      "透露 时 0.9090909090909091\n",
      "手续费 透露 0.9090909090909091\n",
      "具体 需要 0.9166666666666666\n"
     ]
    }
   ],
   "source": [
    "similarity_matrix = pd.DataFrame(data=np.zeros((len(context2.keys()),len(context2.keys()))),index=list(context2.keys()),columns=list(context2.keys()))\n",
    "for row in similarity_matrix.index:\n",
    "    for col in similarity_matrix.columns:\n",
    "        if row!=col:\n",
    "            similarity_matrix.loc[row,col]=len(context2[row]&context2[col])/len(context2[row]|context2[col])\n",
    "print(\"below are the found similar words with window size 2, left2 and right2\")\n",
    "for i,row in enumerate(similarity_matrix.index):\n",
    "    for j,col in enumerate(similarity_matrix.columns):\n",
    "        if i>j:\n",
    "            if similarity_matrix.loc[row,col]>0.9:\n",
    "                print(row,col,similarity_matrix.loc[row,col])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# node2vec is the graph equivalent of word2vec. The difference is that I run the algorithm on the same word context graph as the above wordrep."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Computing transition probabilities: 100%|██████████| 181/181 [00:00<00:00, 13659.28it/s]\n"
     ]
    }
   ],
   "source": [
    "node2vec = Node2Vec(G, dimensions=32, walk_length=30, num_walks=200, workers=4)\n",
    "model = node2vec.fit(window=10, min_count=1, batch_words=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView(('PingWest', '品玩', '7', '月', '18', '日讯', '，', '据', '新浪', '科技', '报道', '今天', '美国众议院', '金融服务', '委员会', '针对', 'Facebook', ' ', 'Libra', '举行', '听证会', '所', '担心', '的', '问题', '向', '项目', '负责人', '大卫', '·', '马库斯', '（', 'David', 'Marcus', '）', '发问', '。', '这', '也', '是', '面临', '第二场', '议员', '询问', '第三方', '钱包', '是否', '可以', '整合', '入', 'WhatsApp', '和', 'Messenger', '中', '没有', '正面', '回应', '一', '综合', '昨日', '与', '美国参议院', '证词', '可能', '无法', '“', '如果', '你们', '要', '支付宝', '微信', '支付', '竞争', '那么', '为何', '在', '瑞士', '注册', '？', '篮子', '货币', '挂钩', '”', '默认', '了', '将', '、', '事实', '同时', '再次', '强调', '日内瓦', '不是', '为了', '逃避', '美国', '监管', '表示', '证券', 'ETF', '它', '商品', '但', '我们', '希望', '工具', '不会', '主权', '行使主权', '职责', '显然', '更', '适合', '央行', '对于', '愿意', '遵守', '美国财政部', '制裁', '要求', '并', '阻止', '无论', '会', '上线', '都', '有', '其他', '网络', '出现', '对', '许多', '国家', '来说', '成为', '一种', '非常', '高质量', '数字', '众议院', '如何', '具有', '管制', '/', '地区', '运行', '提问', '称', '不同', '方法', 'Blaine', '发展', '成', '什么样', '金融', '或', '银行', '服务', '需要', '时', '加密', 'Calibra', '合作', '现在', '讨论', '这个', '为时过早', '透露', '有人', '试图', '把', '兑换', '为', '美元', '产生', '少量', '手续费', '具体', '多少', '取决于', '交易所'))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compare_words(w1,w2,model=model):\n",
    "    return cosine(model.wv.get_vector(w1),model.wv.get_vector(w2))\n",
    "def get_top_similar_words(w,words,k=5,model=model):\n",
    "    distances = []\n",
    "    for tw in words:\n",
    "        if tw!=w:\n",
    "            distances.append([tw,compare_words(w,tw)])\n",
    "    results = pd.DataFrame(data=distances,columns=[\"top_{}_words\".format(k),\"scores\"])\n",
    "    return results.sort_values([\"scores\"])[:k]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# as we can see the two location words come very close to each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0017662644386291504"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"日内瓦\",\"瑞士\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# and the top5 words for 表示 makes some sense too"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>瑞士</td>\n",
       "      <td>0.001766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>具有</td>\n",
       "      <td>0.465970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>挂钩</td>\n",
       "      <td>0.651689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>和</td>\n",
       "      <td>0.708409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>强调</td>\n",
       "      <td>0.744496</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "76           瑞士  0.001766\n",
       "140          具有  0.465970\n",
       "81           挂钩  0.651689\n",
       "51            和  0.708409\n",
       "90           强调  0.744496"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words('日内瓦',list(G.nodes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# gcn untrained\n",
    "这一部分使用未训练的gcn来得到词嵌入。因为原文里边使用未训练的gcn在跆拳道俱乐部图上得到了已经开始聚合的图嵌入。所以这个地方我也想使用未训练的gcn来得到词嵌入。因为没有训练，所以对结果期待不高。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "indeces = list(G.nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gcn_layer(dad,inputs,dims=len(G.nodes())):\n",
    "    \"\"\"\n",
    "    一个gcn层，提前算好的D*A*D（DAD）。\n",
    "    \"\"\"\n",
    "    params = np.random.random(size=(dims,dims))\n",
    "    outputs = dad.dot(inputs).dot(params)\n",
    "    return outputs\n",
    "def gcn_embed(n_gcn=2):\n",
    "    \"\"\"\n",
    "    gcn模型，先计算了DAD。初始的输入为单位矩阵。\n",
    "    \"\"\"\n",
    "    np.random.seed(0)\n",
    "    adj = nx.adjacency_matrix(G,G.nodes()).toarray()\n",
    "    adj = adj+np.eye(adj.shape[0])\n",
    "    dad = adj.dot(np.diag(np.power(adj.sum(1),-0.5))).T.dot(np.diag(np.power(adj.sum(1),-0.5)))\n",
    "    #inputs = np.ones((dad.shape[0],50))\n",
    "    #inputs = np.random.random((dad.shape[0],50))\n",
    "    inputs = np.diag(np.ones(len(G.nodes())))\n",
    "    for _ in range(n_gcn):\n",
    "        inputs = gcn_layer(dad,inputs)\n",
    "    return inputs\n",
    "def get_gcn_embedding(n_gcn,indeces=indeces):\n",
    "    \"\"\"\n",
    "    一个获取gcn词嵌入的帮助函数。\n",
    "    \"\"\"\n",
    "    embeddings = gcn_embed(n_gcn)\n",
    "    gcn_embeddings = {}\n",
    "    for i,e in zip(indeces,embeddings):\n",
    "        gcn_embeddings[i]=e\n",
    "    return gcn_embeddings\n",
    "def compare_words(w1,w2,embeddings):\n",
    "    \"\"\"\n",
    "    一个就是余弦距离的帮助函数。\n",
    "    \"\"\"\n",
    "    return (cosine(embeddings[w1],embeddings[w2])+1)/2\n",
    "def get_top_similar_words(w,embeddings,k=5,reverse=False):\n",
    "    \"\"\"\n",
    "    一个计算前多少个最相近词的帮助函数。\n",
    "    \"\"\"\n",
    "    distances = []\n",
    "    for tw in embeddings.keys():\n",
    "        if tw!=w:\n",
    "            distances.append([tw,compare_words(w,tw,embeddings)])\n",
    "    results = pd.DataFrame(data=distances,columns=[\"top_{}_words\".format(k),\"scores\"])\n",
    "    if reverse:\n",
    "        return results.sort_values([\"scores\"])[-k:]\n",
    "    return results.sort_values([\"scores\"])[:k]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "gcn_embeddings = get_gcn_embedding(5,indeces)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.500000000000002"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>瑞士</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>具有</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>如何</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>在</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>面临</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words  scores\n",
       "76           瑞士     0.5\n",
       "140          具有     0.5\n",
       "139          如何     0.5\n",
       "75            在     0.5\n",
       "40           面临     0.5"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"日内瓦\",gcn_embeddings,k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# training gcn with jieba pos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs = [word_pos[w] for w in list(G.nodes())]\n",
    "o2id = {o:i for i,o in enumerate(set(outputs))}\n",
    "outputs = [o2id[o] for o in outputs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GCN_EMBEDDER(nn.Module):\n",
    "    def __init__(self,G,vocab_size,embedding_size,output_size,n_gcn):\n",
    "        super(GCN_EMBEDDER,self).__init__()\n",
    "        adj = nx.adjacency_matrix(G,G.nodes()).toarray()\n",
    "        adj = adj+np.eye(adj.shape[0])\n",
    "        adj = adj.dot(np.diag(np.power(adj.sum(1),-0.5))).T.dot(np.diag(np.power(adj.sum(1),-0.5)))\n",
    "        self.adj = torch.FloatTensor(adj)\n",
    "        self.gcn_params = [nn.Linear(embedding_size,embedding_size) for _ in range(n_gcn)]\n",
    "        self.projection = nn.Linear(embedding_size,output_size)\n",
    "        self.embedding_size = embedding_size\n",
    "        self.relu = F.relu\n",
    "        self.dropout = nn.Dropout(0.1)\n",
    "        self.norm = nn.BatchNorm1d(embedding_size)\n",
    "        self.input_embedder = nn.Embedding(vocab_size,embedding_size)\n",
    "    \n",
    "    def gcn_layer(self,inputs):\n",
    "        return torch.matmul(self.adj,inputs)\n",
    "    def embed(self,inputs):\n",
    "        inputs = self.input_embedder(inputs)\n",
    "        for l in self.gcn_params:\n",
    "            inputs = l(self.norm(self.relu(self.gcn_layer(inputs))))\n",
    "        return inputs\n",
    "    def forward(self,inputs):\n",
    "        out = self.embed(inputs)\n",
    "        out = self.relu(self.projection(out))\n",
    "        log_probs = F.log_softmax(out,dim=1)\n",
    "        return log_probs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [],
   "source": [
    "words = list(G.nodes)\n",
    "np.random.shuffle(words)\n",
    "w2id = {w:i for i,w in enumerate(words)}\n",
    "id2w = {i:w for i,w in enumerate(words)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gcn_embedder(n_gcn=2,epochs=10):\n",
    "    torch.manual_seed(1)\n",
    "    np.random.seed(1)\n",
    "    gcn_embedder = GCN_EMBEDDER(G,len(G.nodes),50,len(set(outputs)),n_gcn)\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gcn_embedder.parameters(),lr=0.001)\n",
    "    \n",
    "    for e in range(epochs):\n",
    "        inputs = torch.LongTensor([w2id[w] for w in list(G.nodes)])\n",
    "        out = gcn_embedder(inputs)\n",
    "        loss = loss_function(out,torch.LongTensor(outputs))\n",
    "        losses.append(float(loss.data.numpy()))\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if e%31==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gcn_embeddings = {}\n",
    "    for i,e in zip(indeces,gcn_embedder.embed(torch.LongTensor([w2id[w] for w in list(G.nodes)])).data.numpy()):\n",
    "        gcn_embeddings[i]=e\n",
    "    pd.Series(losses).plot();\n",
    "    return gcn_embeddings,losses,gcn_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 3.14\n",
      "epoch 31 has loss 2.94\n",
      "epoch 62 has loss 2.70\n",
      "epoch 93 has loss 2.40\n",
      "epoch 124 has loss 2.09\n",
      "epoch 155 has loss 1.81\n",
      "epoch 186 has loss 1.55\n",
      "epoch 217 has loss 1.32\n",
      "epoch 248 has loss 1.12\n",
      "epoch 279 has loss 0.96\n",
      "epoch 310 has loss 0.84\n",
      "epoch 341 has loss 0.73\n",
      "epoch 372 has loss 0.64\n",
      "epoch 403 has loss 0.55\n",
      "epoch 434 has loss 0.48\n",
      "epoch 465 has loss 0.43\n",
      "epoch 496 has loss 0.36\n",
      "epoch 527 has loss 0.32\n",
      "epoch 558 has loss 0.29\n",
      "epoch 589 has loss 0.27\n",
      "epoch 620 has loss 0.25\n",
      "epoch 651 has loss 0.24\n",
      "epoch 682 has loss 0.23\n",
      "epoch 713 has loss 0.22\n",
      "epoch 744 has loss 0.21\n",
      "epoch 775 has loss 0.21\n",
      "epoch 806 has loss 0.21\n",
      "epoch 837 has loss 0.20\n",
      "epoch 868 has loss 0.19\n",
      "epoch 899 has loss 0.20\n",
      "epoch 930 has loss 0.20\n",
      "epoch 961 has loss 0.20\n",
      "epoch 992 has loss 0.19\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gcn_embeddings,losses,gcn_embedder = train_gcn_embedder(epochs=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6277064681053162"
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.627706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>默认</td>\n",
       "      <td>0.650872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>入</td>\n",
       "      <td>0.662318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>无论</td>\n",
       "      <td>0.673443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>如果</td>\n",
       "      <td>0.686127</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "146           称  0.627706\n",
       "83           默认  0.650872\n",
       "49            入  0.662318\n",
       "121          无论  0.673443\n",
       "66           如果  0.686127"
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 验证了一下adj矩阵行不行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "indeces = list(G.nodes)\n",
    "gcn_embeddings = {}\n",
    "for i,e in zip(indeces,gcn_embedder.adj.data.numpy()):\n",
    "    gcn_embeddings[i]=e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8161186724901199"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>注册</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>具有</td>\n",
       "      <td>0.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>瑞士</td>\n",
       "      <td>0.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>在</td>\n",
       "      <td>0.859729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PingWest</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "77           注册  0.750000\n",
       "140          具有  0.833333\n",
       "76           瑞士  0.833333\n",
       "75            在  0.859729\n",
       "0      PingWest  1.000000"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"日内瓦\",gcn_embeddings,k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# training gcn on a skip-gram setting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [],
   "source": [
    "context1_ids = {}\n",
    "for k in context1.keys():\n",
    "    context1_ids[k] = [w2id[w] for w in context1[k]]\n",
    "def spit_context(w,contexts):\n",
    "    return np.random.choice(contexts[w])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gcn_embedder(n_gcn=2,epochs=10,batchs=3):\n",
    "    torch.manual_seed(0)\n",
    "    np.random.seed(0)\n",
    "    nodes = list(G.nodes())\n",
    "    gcn_embedder = GCN_EMBEDDER(G,len(G.nodes),300,len(nodes),n_gcn)\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gcn_embedder.parameters(),lr=0.001)\n",
    "    for e in range(epochs):\n",
    "        for b in range(batchs):\n",
    "            outputs = [spit_context(w,context1_ids) for w in nodes]\n",
    "            inputs = torch.LongTensor([w2id[w] for w in nodes])\n",
    "            gcn_embedder.zero_grad()\n",
    "            out = gcn_embedder(inputs)\n",
    "            loss = loss_function(out,torch.LongTensor(outputs))\n",
    "            losses.append(float(loss.data.numpy()))\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "        if e%7==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gcn_embeddings = {}\n",
    "    for i,e in zip(indeces,gcn_embedder(inputs).data.numpy()):\n",
    "        gcn_embeddings[i]=e\n",
    "    pd.Series(losses).plot();\n",
    "    return gcn_embeddings,losses,gcn_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 5.17\n",
      "epoch 7 has loss 4.72\n",
      "epoch 14 has loss 4.14\n",
      "epoch 21 has loss 3.51\n",
      "epoch 28 has loss 3.20\n",
      "epoch 35 has loss 3.02\n",
      "epoch 42 has loss 2.71\n",
      "epoch 49 has loss 2.55\n",
      "epoch 56 has loss 2.41\n",
      "epoch 63 has loss 2.40\n",
      "epoch 70 has loss 2.51\n",
      "epoch 77 has loss 2.30\n",
      "epoch 84 has loss 2.20\n",
      "epoch 91 has loss 2.00\n",
      "epoch 98 has loss 2.40\n",
      "epoch 105 has loss 2.09\n",
      "epoch 112 has loss 2.37\n",
      "epoch 119 has loss 2.35\n",
      "epoch 126 has loss 2.15\n",
      "epoch 133 has loss 2.12\n",
      "epoch 140 has loss 2.14\n",
      "epoch 147 has loss 2.07\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gcn_embeddings,losses,gcn_embedder = train_gcn_embedder(n_gcn=2,epochs=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.500415027141571"
      ]
     },
     "execution_count": 367,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.500415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>同时</td>\n",
       "      <td>0.501201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>默认</td>\n",
       "      <td>0.501223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>没有</td>\n",
       "      <td>0.501387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>·</td>\n",
       "      <td>0.502187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "146           称  0.500415\n",
       "88           同时  0.501201\n",
       "83           默认  0.501223\n",
       "54           没有  0.501387\n",
       "29            ·  0.502187"
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gcn_embeddings,k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# build GCN layerwise jieba tag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GC_Layer(nn.Module):\n",
    "    def __init__(self,G,input_size,output_size):\n",
    "        super(GC_Layer,self).__init__()\n",
    "        adj = nx.adjacency_matrix(G,G.nodes()).toarray()\n",
    "        adj = adj+np.eye(adj.shape[0])\n",
    "        adj = adj.dot(np.diag(np.power(adj.sum(1),-0.5))).T.dot(np.diag(np.power(adj.sum(1),-0.5)))\n",
    "        self.adj = torch.FloatTensor(adj)\n",
    "        self.project = nn.Linear(input_size,output_size)\n",
    "        \n",
    "    def agg(self,inputs):\n",
    "        return torch.mm(self.adj,inputs)\n",
    "    def forward(self,inputs):\n",
    "        agged = self.agg(inputs)\n",
    "        projected = self.project(agged)\n",
    "        return projected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GCN_Embedder(nn.Module):\n",
    "    def __init__(self,G,hidden_gc_dim,gc_out_dim,n_classes):\n",
    "        super(GCN_Embedder,self).__init__()\n",
    "        self.gc_1 = GC_Layer(G,len(G.nodes()),hidden_gc_dim)\n",
    "        self.gc_2 = GC_Layer(G,hidden_gc_dim,gc_out_dim)\n",
    "        self.project = nn.Linear(gc_out_dim,n_classes)\n",
    "        self.norm = nn.BatchNorm1d(gc_out_dim)\n",
    "        \n",
    "    def embed(self,inputs):\n",
    "        inputs = self.gc_1(inputs)\n",
    "        return self.gc_2(inputs)\n",
    "    def forward(self,inputs):\n",
    "        inputs = self.embed(inputs)\n",
    "        out = self.project(self.norm(inputs))\n",
    "        return F.log_softmax(out,dim=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gcn_embedder(epochs=10):\n",
    "    torch.manual_seed(0)\n",
    "    np.random.seed(0)\n",
    "    gcn_embedder = GCN_Embedder(G,100,50,len(set(outputs)))\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gcn_embedder.parameters(),lr=0.001)\n",
    "    \n",
    "    for e in range(epochs):\n",
    "        inputs = torch.eye(len(G.nodes()))\n",
    "        out = gcn_embedder(inputs)\n",
    "        loss = loss_function(out,torch.LongTensor(outputs))\n",
    "        losses.append(float(loss.data.numpy()))\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if e%31==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gcn_embeddings = {}\n",
    "    for i,e in zip(indeces,gcn_embedder.embed(torch.eye(len(G.nodes()))).data.numpy()):\n",
    "        gcn_embeddings[i]=e\n",
    "    pd.Series(losses).plot();\n",
    "    return gcn_embeddings,losses,gcn_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 3.24\n",
      "epoch 31 has loss 1.74\n",
      "epoch 62 has loss 1.02\n",
      "epoch 93 has loss 0.56\n",
      "epoch 124 has loss 0.27\n",
      "epoch 155 has loss 0.17\n",
      "epoch 186 has loss 0.14\n",
      "epoch 217 has loss 0.11\n",
      "epoch 248 has loss 0.08\n",
      "epoch 279 has loss 0.09\n",
      "epoch 310 has loss 0.03\n",
      "epoch 341 has loss 0.07\n"
     ]
    },
    {
     "data": {
      "image/png": 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JqdxHUGVFITefP4Elr+xgfZ2uuSoiw0flPsI+v2g6RbkZ3PPkWrp7NPddRIaHyn2EFWSFuO8Ds1hf18yjr+70O46IJCmVuw+unlPKwuklfO0PW9jZeMTvOCKShFTuPjAzvnzDHEJpxj/9Yg09vbpqk4jElsrdJ6UFmXxx8Syqdh1iySs677uIxJbK3UfXzy3nL2eO4b//sIWt+1v8jiMiSWTIcjezR8ys3szWD/K6mdkDZlZjZmvNbF7sYyanY8MzuRlBPveLNZo9IyIxE82W+6PAohO8fhUw1bvdDjx4+rFSRzgvgy9dP5u1tU08+KdtfscRkSQxZLk7514GDp5gkcXAYy7idWCUmZXFKmAquHpOGdedPZZv/nEr62p1cJOInL5YjLmXA7v7PK71npOTcP/iWYTzMrjribc40qFzz4jI6RnRHapmdruZVZlZVUODLj3X16jsdL7xkbnsOnCEe39d7XccEUlwsSj3OmB8n8fjvOfewzn3kHOu0jlXGQ6HY/DRyWXB5CLuvHwqv3qzlqffGnAViohEJRblvhT4mDdrZgHQ5JzbG4P3TUl3XT6Fyomj+cLT69l1QEevisipiWYq5OPAa8A0M6s1s4+b2R1mdoe3yDPAdqAG+AHw6WFLmwKCaQH+56a5BAzuevwtXVhbRE5JcKgFnHN/PcTrDvhMzBIJ40Zn89Ubz+JTP32T/3puE1+4dqbfkUQkwegI1Th11ZwyPnbBRB5+ZQfPrNMol4icHJV7HPvCNTM5Z8Io/vkXa6ip1+kJRCR6Kvc4lh4M8N2/mUdWehq3/3gVLe1dfkcSkQShco9zZQVZfOuv57HrwFH++RdrieziEBE5MZV7ArjgjCLuWTSd56r36eLaIhKVIWfLSHz4xCWT2FrfwgMv1jCxKIcbzx3ndyQRiWPack8QZsaXrp/DBZOLuOfJtazYfsDvSCISx1TuCSQ9GOB7Hz2X8YXZfPInq9ih66+KyCBU7gmmIDvED287j4AZH314BXub2vyOJCJxSOWegCYW5fCjv51PU1sXf/PwChpbO/yOJCJxRuWeoOaMK+CR285jz+E2blmykqajmgMvIu9QuSew+ZMKeeiWSrbVt3LrD1fS1KaCF5EIlXuCu/TMMN+6+Ryq9zRx8w9e1xCNiAAq96Rw5axSHvpYJdsaWvnw919jz2HtZBVJdSr3JPH+aSU89n/Op6G5gw997zW2N7T6HUlEfKRyTyLzJxXy+O0LaOvq4Ybvvspr23Sgk0iqUrknmdnlBTz16QsJ52Vwy5IVPLHybb8jiYgPVO5JaGJRDk9++kIunFLMPU+u4z9/u4HuHl2uTySVqNyTVH5miEdureS2CytY8soObn54Bfub2/2OJSIjROWexIJpAe67bhbf+MjZrKtt4poHlvPnmka/Y4nICFC5p4AbzhnH0jsvYnR2Oh9dsoIH/riVnl5d9EMkmancU8TUMXn8+s6LuH5uOV9/fgu3LNEwjUgyi6rczWyRmW02sxozu2eA128zswYzW+3dPhH7qHK6stODfP3DZ/NfN57FW28fZtH/vMwLG/b7HUtEhsGQ5W5macB3gKuAmcBfm9nMARb9mXNurnd7OMY5JUbMjA+fN57f3nUxZQVZfOKxKu799Xrau3r8jiYiMRTNlvt8oMY5t9051wk8ASwe3lgy3M4I5/LUZy7k4xdP4rHXdrH4239my/4Wv2OJSIxEU+7lwO4+j2u95/q70czWmtkvzWx8TNLJsMoIpvHv187k0b89jwNHOvjAt17hJ6/vwjntbBVJdLHaofoboMI5dxbwPPCjgRYys9vNrMrMqhoaGmL00XK6LptWwrN3X8r5k4v4wtPr+eSPV3HoSKffsUTkNERT7nVA3y3xcd5zxznnDjjnjp1r9mHg3IHeyDn3kHOu0jlXGQ6HTyWvDJNwXgaP3nYeX7hmBss213PVN5fr3DQiCSyacn8DmGpmk8wsHbgJWNp3ATMr6/PwOmBj7CLKSAkEjE9cMpmnPn0R2elp3Pzw6/z37zfTpVMXiCScIcvdOdcN3An8nkhp/9w5V21m95vZdd5id5lZtZmtAe4CbhuuwDL8ZpcX8Ju/v5gPzhvHt5fV8OHvv8bug0f9jiUiJ8H82nlWWVnpqqqqfPlsid5v1uzhX59cB8CXbpjN4rkD7UsXkZFiZqucc5VDLacjVOWEPnD2WJ65+xKmjsnl7idW87mfr6G1o9vvWCIyBJW7DGl8YTY//+QF3HX5FJ56q5ZrH1jO2trDfscSkRNQuUtUgmkB/vEvp/H43y2go7uXGx98le+/tI1enYBMJC6p3OWknD+5iGfvvoSF08fwlWc3cesPV+oEZCJxSOUuJ21UdjoPfnQeX75hNm/sPMjCr73Ew8u3a8qkSBxRucspMTP+5vyJPHv3pVRWjOZLv9vINQ8s54UN+3X6ApE4oHKX0zKpOIcf3nYeD91yLp3dvXzisSqu/+6rLNtUr/F4ER9pnrvETHdPL0++Wcc3/7iVusNtVBRl89EFE1k8t5xwXobf8USSQrTz3FXuEnOd3b08V72Px17dSdWuQ5hB5cTRXD59DGePL2B2eQH5mSG/Y4okJJW7xIXN+1p4dv1e/lC9nw17m48/X5ybQXFuOuG8DAqyQuRnhcjPDJGfFSQ/M0RBVogpJblMLcklmKbRQ5Fjoi334EiEkdQ1rTSPaaV5fPaKM2ls7aB6TzPr65qoPXSUhpZOGls7qDvcRnNbN81tXXT2m3GTEQxw1rgCrpgxhitnlVJRnOPTf4lIYtGWu8SV9q4emtu7OHSki037mllX28Rr2w9QvSey1T9rbD43nFPOdWePpSQ/0+e0IiNPwzKSVHYfPMrvq/exdM0e1tY2ETC4aEoxN5xTzpWzSsnJ0JdQSQ0qd0laNfWt/Hp1HU+9VUftoTayQmlcOWsM159TzsVTijVGL0lN5S5Jr7fXsertQzz1Vh2/W7uXprYuinPTuWRqmPMnFbJgchETi7IxM7+jisSMyl1SSkd3D3/a3MBv1uzh9e0HaGyNXAO2ODeDOeX5zC6PTMGcNTafsQVZBAIqfElMmi0jKSUjmMaVs0q5clYpzjm2NRzhte0HWP32YdbXNfHSlgaOHTCbGQpQUZRDRVEOpQWZjM5OZ3ROiLzMIGmBAAGDgBldPb20d/XQ1tlDe3dv5GdX5NbR3Utndy8dPb10dffS2RN5fOz8OmkBI5QWIC1gBAMBMkKByFTPzCD5WZHPKsgKEc7NoCQ/g3BuJvlZQX3LkJhRuUvSMTOmlOQypSSXWxZMBKCts4eN+5rZsKeZHY1H2Nl4hC31Lfy5ppGWk7j4SEYwQGYojYxggPRjt7R3foa88f6eXseR7m66ex3dPc6bBdRNc3sXnd0Dn2AtPRggnJtBOC+DkrzIzzH5mZQWZFJ2/JalnccSFf2WSErISk9j3oTRzJsw+j2vdfX00tTWRXNbF73O4Rz0OEcoLVLkWd4tIxiIyXBOe1cPLe3dNLV1Ut/SQUP/W2sHuw4c5Y2dBzl0tOs9/z4vM0hZQSalBVmU5WcybnQWE4qyGV+YzYTCbIpy0of1G0B7V8/xnA0tHdS3dNDY0kFbVw9dPZFvL85BViiN7PQ0stKDFOaEKMnPpCQvg7EFWYzOSR+2fBKhcpeUF0oLeEfMjsz5bzJDaWSG0gjnZTClJO+Ey3Z097C/qYO9TW3sa25nb1M7+5raI4+b2tm4t5mGlo53/Zvs9DQmFL5T9sdu4wuzGDc6m8xQ2ruW7+l1HO3spqmtiwOtkQPLDrR20nikg0bvQLNIibfT0NJBc/vA33QyQ5FvLqG0AAa0dfXQ1tXDQLv1RmWHmFycw+RwLmeEc5k5Np855QUUJmHp9/Y6Drd19fnj3c7k4lzOHj9qWD9X5S4SxzKCaUwoymZCUfagy7R39VB76ChvHzzK2weO8vbBtuP3X9naSFtXz7uWz0lPI5gW2bfQ3tX7ntf7L1vsDRNNK83j4inF3rBRJmFv6Cicl0FRTvqAU1Cdc7R19XCgtZP6lnbqmyNHJG9rOML2hlZe2tLAL1fVHl++fFQWc8oLmDOugDneTvB4LvzeXkfjkQ72HG5nz+E29hxuo877ubcp8t/b2NpBd78zpP7dJZNU7iJyYpmhNKaU5A34LcA5R2NrJ28fPMrug5E/AE1tXfT0Orp7e8kKpZGTESQnPUh+VpDi3AyKvPP+FOVkkJWeNsAnRs/MyE4Pkl0YZHzhwH+gmtq6qN7TxLraJtbVRW7PVe87/npZQSazxkZmOs0am8/00nzKR2eRNgIznjq6e9hzuJ3aQ0epO3SsvL0ib2pj7+H295wyIzs9jfJRWZSNymLamLx3/RE8tk9lzAgcXR3VVEgzWwR8E0gDHnbO/b9+r2cAjwHnAgeAjzjndp7oPTUVUkQG09TWxfq6Jqr3NFG9p5nqPc1sb2g9PuMplGZMKMxmUnEOk4pzqCjOYUJhNmPyMxmTn0l+5tAzj452dnOgtZODRzo54G191x1uo/ZQ2/Eyr+835BUwGJOfydhRWd4tk/JRWYwtiDwuH5U17LOeYjYV0szSgO8AfwHUAm+Y2VLn3IY+i30cOOScm2JmNwFfBT5yatFFJNUVZIW4aEoxF00pPv7c0c5uNu1roaa+lR2NR9jRcISdB46wfGsjHf1mIGWGAmSnB4/PbjKgw5uq2tkTmdba/99A5I/GsZJ+35lhxo3Opnx0FuNGR54rLcg8PiMq3kUzLDMfqHHObQcwsyeAxUDfcl8M3Ofd/yXwbTMzp+utiUiMZKcHB5zx1Nvr2NvcTt2hyE7n/U3tNLR2HD8uoaO7l17nSA8GIlNYvVlQo3PSKcxOpzAnncLcdMYWZBHOyxiR4Z6REE25lwO7+zyuBc4fbBnnXLeZNQFFQGMsQoqIDCYQMMq9rW15x4h+vzCz282sysyqGhoaRvKjRURSSjTlXgeM7/N4nPfcgMuYWRAoILJj9V2ccw855yqdc5XhcPjUEouIyJCiKfc3gKlmNsnM0oGbgKX9llkK3Ord/yDwosbbRUT8M+SYuzeGfifweyJTIR9xzlWb2f1AlXNuKbAE+LGZ1QAHifwBEBERn0R1EJNz7hngmX7P3dvnfjvwodhGExGRU5UYEzZFROSkqNxFRJKQyl1EJAn5dpk9M2sAdp3iPy8msQ6QUt7hk0hZIbHyJlJWSJ28E51zQ84l963cT4eZVUVz4px4obzDJ5GyQmLlTaSsoLz9aVhGRCQJqdxFRJJQopb7Q34HOEnKO3wSKSskVt5EygrK+y4JOeYuIiInlqhb7iIicgIJV+5mtsjMNptZjZnd43eegZjZTjNbZ2arzazKe67QzJ43s63ez9FDvc8wZXvEzOrNbH2f5wbMZhEPeOt6rZnNi5O895lZnbd+V5vZ1X1e+xcv72Yzu3KEs443s2VmtsHMqs3sbu/5uFy/J8gbd+vXzDLNbKWZrfGyftF7fpKZrfAy/cw7uSFmluE9rvFerxiprEPkfdTMdvRZt3O952P/u+CcS5gbkROXbQMmA+nAGmCm37kGyLkTKO733H8B93j37wG+6lO2S4F5wPqhsgFXA88CBiwAVsRJ3vuAfxpg2Zne70QGMMn7XUkbwaxlwDzvfh6wxcsUl+v3BHnjbv166yjXux8CVnjr7OfATd7z3wM+5d3/NPA97/5NwM9GeN0OlvdR4IMDLB/z34VE23I/fsk/51wncOySf4lgMfAj7/6PgOv9COGce5nImTv7GizbYuAxF/E6MMrMykYmacQgeQezGHjCOdfhnNsB1BD5nRkRzrm9zrk3vfstwEYiVymLy/V7gryD8W39euuo1XsY8m4OuJzIpT3hvev22Dr/JbDQbBivWt3PCfIOJua/C4lW7gNd8u9Ev4x+ccAfzGyVmd3uPTfGObfXu78PGONPtAENli2e1/ed3tfXR/oMccVNXm8Y4BwiW2xxv3775YU4XL9mlmZmq4F64Hki3xwOO+e6B8jzrkt/Ascu/Tli+ud1zh1bt1/21u03zCyjf17Paa/bRCv3RHGxc24ecBXwGTO7tO+LLvI9LC6nKcVztj4eBM4A5gJ7ga/5G+fdzCwX+BXwWedcc9/X4nH9DpCLD7DtAAAB5UlEQVQ3Ltevc67HOTeXyNXg5gPTfY50Qv3zmtls4F+I5D4PKAQ+P1yfn2jlHs0l/3znnKvzftYDTxH5Rdx/7GuW97Pev4TvMVi2uFzfzrn93v84vcAPeGdowPe8ZhYiUpQ/dc496T0dt+t3oLzxvH69fIeBZcAFRIYvjl2Xom+eqC79ORL65F3kDYU551wH8EOGcd0mWrlHc8k/X5lZjpnlHbsP/CWwnndfivBW4Nf+JBzQYNmWAh/z9uQvAJr6DC/4pt9Y5A1E1i9E8t7kzZSYBEwFVo5gLiNyVbKNzrmv93kpLtfvYHnjcf2aWdjMRnn3s4C/ILKPYBmRS3vCe9etb5f+HCTvpj5/5I3I/oG+6za2vwvDvdc41jcie5W3EBlv+ze/8wyQbzKRGQVrgOpjGYmM9/0R2Aq8ABT6lO9xIl+1u4iM6318sGxE9tx/x1vX64DKOMn7Yy/PWu9/irI+y/+bl3czcNUIZ72YyJDLWmC1d7s6XtfvCfLG3foFzgLe8jKtB+71np9M5A9MDfALIMN7PtN7XOO9PnmE1+1geV/01u164Ce8M6Mm5r8LOkJVRCQJJdqwjIiIREHlLiKShFTuIiJJSOUuIpKEVO4iIklI5S4ikoRU7iIiSUjlLiKShP4/R921hvvPTQoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gcn_embeddings,losses,gcn_embedder = train_gcn_embedder(epochs=350)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5714088380336761"
      ]
     },
     "execution_count": 374,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.571409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>和</td>\n",
       "      <td>0.586082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>默认</td>\n",
       "      <td>0.588989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>发问</td>\n",
       "      <td>0.595599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>需要</td>\n",
       "      <td>0.596417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "146           称  0.571409\n",
       "51            和  0.586082\n",
       "83           默认  0.588989\n",
       "35           发问  0.595599\n",
       "157          需要  0.596417"
      ]
     },
     "execution_count": 375,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gcn_embeddings,k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# skip_gram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gcn_embedder(epochs=10):\n",
    "    torch.manual_seed(0)\n",
    "    np.random.seed(0)\n",
    "    gcn_embedder = GCN_Embedder(G,100,50,len(G.nodes()))\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gcn_embedder.parameters(),lr=0.001)\n",
    "    nodes = list(G.nodes())\n",
    "    for e in range(epochs):\n",
    "        inputs = torch.eye(len(G.nodes()))\n",
    "        outputs = [spit_context(w,context1_ids) for w in nodes]\n",
    "        out = gcn_embedder(inputs)\n",
    "        loss = loss_function(out,torch.LongTensor(outputs))\n",
    "        losses.append(float(loss.data.numpy()))\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if e%31==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gcn_embeddings = {}\n",
    "    for i,e in zip(indeces,gcn_embedder.embed(torch.eye(len(G.nodes()))).data.numpy()):\n",
    "        gcn_embeddings[i]=e\n",
    "    pd.Series(losses).plot();\n",
    "    return gcn_embeddings,losses,gcn_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 5.27\n",
      "epoch 31 has loss 4.25\n",
      "epoch 62 has loss 3.55\n",
      "epoch 93 has loss 2.74\n",
      "epoch 124 has loss 2.23\n",
      "epoch 155 has loss 1.96\n",
      "epoch 186 has loss 1.81\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gcn_embeddings,losses,gcn_embedder = train_gcn_embedder(epochs=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5088319480419159"
      ]
     },
     "execution_count": 384,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"表示\",\"称\",gcn_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.508832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>没有</td>\n",
       "      <td>0.521774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>马库斯</td>\n",
       "      <td>0.526738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>默认</td>\n",
       "      <td>0.534633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>昨日</td>\n",
       "      <td>0.537473</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words    scores\n",
       "146           称  0.508832\n",
       "54           没有  0.521774\n",
       "30          马库斯  0.526738\n",
       "83           默认  0.534633\n",
       "59           昨日  0.537473"
      ]
     },
     "execution_count": 385,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gcn_embeddings,k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# build GAT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Gat(nn.Module):\n",
    "    def __init__(self,g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool):\n",
    "        super(Gat,self).__init__()\n",
    "        self.g = g\n",
    "        self.adj = nx.adjacency_matrix(g,g.nodes())\n",
    "        srcs,tgts = self.adj.nonzero()\n",
    "        neighbors = {i:[] for i in range(self.adj.shape[0])}\n",
    "        neighbor_targets = {i:[] for i in range(self.adj.shape[0])}\n",
    "        self.node_size = len(g.nodes())\n",
    "        for i,j,t in zip(srcs,range(len(srcs)),tgts):\n",
    "            neighbors[i].append(j)\n",
    "            neighbor_targets[i].append(t)\n",
    "        self.neighbors = neighbors\n",
    "        self.neighbor_targets = neighbor_targets\n",
    "        self.neighbor_pairs = [(i,j) for i,j in zip(srcs,tgts)]\n",
    "        self.projector0s = [nn.Linear(self.node_size,hidden_dim,bias=False)\n",
    "                           for _ in range(heads)]\n",
    "        self.projector1s = [nn.Linear(2*hidden_dim,1,bias=False)\n",
    "                           for _ in range(heads)]\n",
    "        self.softmax = F.softmax\n",
    "        self.leakyRelu = F.leaky_relu\n",
    "        self.elu = F.elu\n",
    "        self.relu = F.relu\n",
    "        self.embedder_layers = [self.embedder_layer(p0,p1) for p0,p1 in \n",
    "                               zip(self.projector0s,self.projector1s)]\n",
    "        self.projector0_out = nn.Linear(hidden_dim*heads,hidden_dim1,bias=False)\n",
    "        self.projector1_out = nn.Linear(2*hidden_dim1,1)\n",
    "        self.embedder_out = self.embedder_layer(self.projector0_out,self.projector1_out)\n",
    "        self.output_projector = nn.Linear(hidden_dim1,out_dim)\n",
    "    def stack_concate_neighbor_pairs(self,nodes):\n",
    "        results = []\n",
    "        for i,j in self.neighbor_pairs:\n",
    "            results.append(torch.cat([nodes[i],nodes[j]]))\n",
    "        return torch.stack(results)\n",
    "    \n",
    "    def get_weights_and_embeddings_blocks_for_i(self,i,nodes,pairs):\n",
    "        return nodes[self.neighbor_targets[i]],pairs[self.neighbors[i]]\n",
    "    \n",
    "    def embedder_layer(self,projector0,projector1):\n",
    "        def embed(nodes):\n",
    "            #nodes = torch.eye(self.node_size)\n",
    "            nodes = projector0(nodes)\n",
    "            pairs = self.stack_concate_neighbor_pairs(nodes)\n",
    "            pairs = projector1(pairs)\n",
    "            pairs = self.leakyRelu(pairs)\n",
    "            output_nodes = []\n",
    "            for i in range(self.node_size):\n",
    "                ith_weights,ith_embeddings = self.get_weights_and_embeddings_blocks_for_i(i,nodes,pairs)\n",
    "                ith_weights = self.softmax(ith_weights)\n",
    "                ith_weights = ith_weights.transpose(1,0)\n",
    "                ith_nodes = torch.matmul(ith_weights,ith_embeddings)\n",
    "                output_nodes.append(ith_nodes)\n",
    "            return torch.squeeze(torch.stack(output_nodes))\n",
    "        return embed\n",
    "    def encode(self):\n",
    "        nodes = torch.eye(self.node_size)\n",
    "        embedded_nodes = []\n",
    "        for el in self.embedder_layers:\n",
    "            embedded_nodes.append(el(nodes))\n",
    "        if mean_pool:\n",
    "            embedded_nodes = torch.stack(embedded_nodes)\n",
    "            embedded_nodes = torch.mean(embedded_nodes,dim=0)\n",
    "            output_nodes = self.elu(embedded_nodes)\n",
    "        else:\n",
    "            embedded_nodes = torch.cat(embedded_nodes,dim=1)\n",
    "            embedded_nodes = self.elu(embedded_nodes)\n",
    "            output_nodes = self.embedder_out(embedded_nodes)\n",
    "        return output_nodes\n",
    "    def flow(self):\n",
    "        output_nodes = self.encode()\n",
    "        outputs = self.output_projector(output_nodes)\n",
    "        outputs = self.relu(outputs)\n",
    "        log_probs = F.log_softmax(outputs,dim=1)\n",
    "        return log_probs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GAT with jieba pos prediction task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs = [word_pos[w] for w in list(G.nodes())]\n",
    "o2id = {o:i for i,o in enumerate(set(outputs))}\n",
    "outputs = [o2id[o] for o in outputs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gat_embedder(g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool,epochs,lr=0.001):\n",
    "    torch.manual_seed(1)\n",
    "    np.random.seed(1)\n",
    "    gat_embedder = Gat(g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool)\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gat_embedder.parameters(),lr=lr)\n",
    "    \n",
    "    for e in range(epochs):\n",
    "        gat_embedder.zero_grad()\n",
    "        out = gat_embedder.flow()\n",
    "        loss = loss_function(out,torch.LongTensor(outputs))\n",
    "        losses.append(float(loss.data.numpy()))\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if e%31==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gat_embeddings = get_embedding_dict(gat_embedder.encode().detach().numpy(),indeces)\n",
    "    pd.Series(losses).plot();\n",
    "    return gat_embeddings,losses,gat_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# helper funcs\n",
    "def get_embedding_dict(embeddings,indeces):\n",
    "    \"\"\"\n",
    "    一个获取gcn词嵌入的帮助函数。\n",
    "    \"\"\"\n",
    "    out_embeddings = {}\n",
    "    for i,e in zip(indeces,embeddings):\n",
    "        out_embeddings[i]=e\n",
    "    return out_embeddings\n",
    "def compare_words(w1,w2,embeddings):\n",
    "    \"\"\"\n",
    "    一个就是余弦距离的帮助函数。\n",
    "    \"\"\"\n",
    "    return (cosine(embeddings[w1],embeddings[w2])+1)/2\n",
    "def get_top_similar_words(w,embeddings,k=5,reverse=False):\n",
    "    \"\"\"\n",
    "    一个计算前多少个最相近词的帮助函数。\n",
    "    \"\"\"\n",
    "    distances = []\n",
    "    for tw in embeddings.keys():\n",
    "        if tw!=w:\n",
    "            distances.append([tw,compare_words(w,tw,embeddings)])\n",
    "    results = pd.DataFrame(data=distances,columns=[\"top_{}_words\".format(k),\"scores\"])\n",
    "    if reverse:\n",
    "        return results.sort_values([\"scores\"])[-k:]\n",
    "    return results.sort_values([\"scores\"])[:k]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 3.16\n",
      "epoch 31 has loss 3.15\n",
      "epoch 62 has loss 3.14\n",
      "epoch 93 has loss 3.14\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = G\n",
    "heads = 1\n",
    "hidden_dim = 50\n",
    "hidden_dim1 = 50\n",
    "out_dim = len(set(outputs))\n",
    "mean_pool = True\n",
    "epochs = 100\n",
    "lr = 0.001\n",
    "gat_embeddings,lossses,gat_embedder = train_gat_embedder(g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool,epochs,lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4999999403953552"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"瑞士\",\"日内瓦\",gat_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>证词</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>来说</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>合作</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>手续费</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words  scores\n",
       "146           称     0.5\n",
       "62           证词     0.5\n",
       "132          来说     0.5\n",
       "161          合作     0.5\n",
       "175         手续费     0.5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gat_embeddings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# train GAT with skip-gram setting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "words = list(G.nodes)\n",
    "np.random.shuffle(words)\n",
    "w2id = {w:i for i,w in enumerate(words)}\n",
    "id2w = {i:w for i,w in enumerate(words)}\n",
    "context1_ids = {}\n",
    "for k in context1.keys():\n",
    "    context1_ids[k] = [w2id[w] for w in context1[k]]\n",
    "def spit_context(w,contexts):\n",
    "    return np.random.choice(contexts[w])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_gat_embedder(g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool,epochs,batchs,lr=0.001):\n",
    "    torch.manual_seed(1)\n",
    "    np.random.seed(1)\n",
    "    nodes = list(G.nodes())\n",
    "    gat_embedder = Gat(g,heads,hidden_dim,hidden_dim1,out_dim,mean_pool)\n",
    "    losses = []\n",
    "    loss_function = nn.NLLLoss()\n",
    "    optimizer = optim.Adam(gat_embedder.parameters(),lr=lr)\n",
    "    \n",
    "    for e in range(epochs):\n",
    "        for b in range(batchs):\n",
    "            outputs = [spit_context(w,context1_ids) for w in nodes]\n",
    "            gat_embedder.zero_grad()\n",
    "            out = gat_embedder.flow()\n",
    "            loss = loss_function(out,torch.LongTensor(outputs))\n",
    "            losses.append(float(loss.data.numpy()))\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "        if e%7==0:\n",
    "            print(\"epoch {} has loss {:.2f}\".format(e,loss))\n",
    "    indeces = list(G.nodes)\n",
    "    gat_embeddings = get_embedding_dict(gat_embedder.encode().detach().numpy(),indeces)\n",
    "    pd.Series(losses).plot();\n",
    "    return gat_embeddings,losses,gat_embedder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0 has loss 5.20\n",
      "epoch 7 has loss 5.19\n",
      "epoch 14 has loss 5.18\n",
      "epoch 21 has loss 5.17\n",
      "epoch 28 has loss 5.17\n",
      "epoch 35 has loss 5.17\n",
      "epoch 42 has loss 5.15\n",
      "epoch 49 has loss 5.16\n",
      "epoch 56 has loss 5.15\n",
      "epoch 63 has loss 5.15\n",
      "epoch 70 has loss 5.15\n",
      "epoch 77 has loss 5.14\n",
      "epoch 84 has loss 5.14\n",
      "epoch 91 has loss 5.14\n",
      "epoch 98 has loss 5.12\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = G\n",
    "heads = 1\n",
    "hidden_dim = 50\n",
    "hidden_dim1 = 50\n",
    "out_dim = len(outputs)\n",
    "mean_pool = True\n",
    "epochs = 100\n",
    "batchs = 3\n",
    "lr = 0.001\n",
    "gat_embeddings,lossses,gat_embedder = train_gat_embedder(g,heads,hidden_dim,\n",
    "                                                         hidden_dim1,out_dim,mean_pool,epochs,batchs,lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4999999403953552"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_words(\"瑞士\",\"日内瓦\",gat_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>top_5_words</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>称</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>证词</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>来说</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>合作</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>手续费</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    top_5_words  scores\n",
       "146           称     0.5\n",
       "62           证词     0.5\n",
       "132          来说     0.5\n",
       "161          合作     0.5\n",
       "175         手续费     0.5"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_top_similar_words(\"表示\",gat_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
